Schiffsbelader
Transport und MaterialbewegungKI-Exposition
- Datenquelle: BLSVeröffentlicht: 2026-08
Niedrig· relativ
NiedrigVier relative BänderSehr hochWert auf Berufsgruppenebene
Skala, Bezugsmenge und Quelle
Vier relative Bänder (Niedrig / Mittel / Hoch / Sehr hoch)
831 detaillierte Berufe in der BLS-Beschäftigungsprojektionstabelle. Der Wert wird je Code der National Employment Matrix (NEM) vergeben, daher erhalten Berufe mit demselben NEM-Code dasselbe Band
- Datenquelle: AnthropicVeröffentlicht: 2026-03
0.000
0.000Spannweite der hier geführten Werte0.745Skala, Bezugsmenge und Quelle
Index der beobachteten Exposition, 0–1 wie veröffentlicht
Auf O*NET-Aufgaben abgebildet
- Datenquelle: ILOVeröffentlicht: 2025
0.14
0.09Spannweite der hier geführten Werte0.70Wert auf Berufsgruppenebene
Skala, Bezugsmenge und Quelle
Index der Exposition gegenüber generativer KI, 0–1 wie veröffentlicht
ISCO-08-Berufsgattung — alle Berufe mit demselben Code erhalten diesen Wert
Von dieser Website berechnet, nicht von der IAO veröffentlicht: Von den 1.012 Berufen, die diese Website mit dem IAO-Datensatz verknüpft, erreichen oder übertreffen 95% diesen Wert.
Welche Art von Wert diese Quelle veröffentlicht
Die Kategorie von BLS ist ein relativer Rang und kein absolutes Niveau, und sie ist keine eigene Messung: Sie fasst die Perzentilränge des Berufs aus mehreren veröffentlichten Studien in vier Bänder zusammen. Sie ist weder eine Beschäftigungs- oder Lohnprognose noch eine Einführungswahrscheinlichkeit und unterscheidet nicht zwischen Automatisierung und Augmentierung.
Task-level exposure
Nur exponierte Aufgaben| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Sort cargo before loading and unloading.53-7062 | 0.00000.0 | —0 |
Read work orders or receive oral instructions to determine work assignments or material or equipment needs. | —0 | 0.0100100.0 |
| Not observed on any surface — 11 task(s) — These tasks have no row in the source for this release. The 0 in the share row is a display-stage composition ratio; absence is what the — in the raw row states. | ||
Move freight, stock, or other materials to and from storage or production areas, loading docks, delivery vehicles, ships, or containers, by hand or using trucks, tractors, or other equipment. | —0 | —0 |
Maintain equipment storage areas to ensure that inventory is protected. | —0 | —0 |
Attach identifying tags to containers or mark them with identifying information. | —0 | —0 |
Record numbers of units handled or moved, using daily production sheets or work tickets. | —0 | —0 |
Assemble product containers or crates, using hand tools and precut lumber. | —0 | —0 |
Pack containers and re-pack damaged containers. | —0 | —0 |
Carry needed tools or supplies from storage or trucks and return them after use. | —0 | —0 |
Install protective devices, such as bracing, padding, or strapping, to prevent shifting or damage to items being transported. | —0 | —0 |
Attach slings, hooks, or other devices to lift cargo and guide loads. | —0 | —0 |
Adjust controls to guide, position, or move equipment, such as cranes, booms, or cameras. | —0 | —0 |
Connect electrical equipment to power sources so that it can be tested before use. | —0 | —0 |
Values in this tab are predicted labels, not observations. Eloundou et al. (2023) published two rating regimes — human raters and GPT-4 — and the β shown here is derived from the GPT-4 rater basis alone; the same task can take a different value under the other regime. The unit and the meaning differ from the observed shares (%) in the other tabs, so do not place them on the same axis.
| Task | βE1 + 0.5 × E2 |
|---|---|
Record numbers of units handled or moved, using daily production sheets or work tickets.O*NET Task ID 10780 | 1.0 |
Attach identifying tags to containers or mark them with identifying information.O*NET Task ID 10778 | 0.0 |
Read work orders or receive oral instructions to determine work assignments or material or equipment needs.O*NET Task ID 10779 | 0.0 |
Move freight, stock, or other materials to and from storage or production areas, loading docks, delivery vehicles, ships, or containers, by hand or using trucks, tractors, or other equipment.O*NET Task ID 10781 | 0.0 |
Sort cargo before loading and unloading.O*NET Task ID 10782 | 0.0 |
Pack containers and re-pack damaged containers.O*NET Task ID 10786 | 0.0 |
Carry needed tools or supplies from storage or trucks and return them after use.O*NET Task ID 10787 | 0.0 |
Install protective devices, such as bracing, padding, or strapping, to prevent shifting or damage to items being transported.O*NET Task ID 10788 | 0.0 |
Maintain equipment storage areas to ensure that inventory is protected.O*NET Task ID 10789 | 0.0 |
Attach slings, hooks, or other devices to lift cargo and guide loads.O*NET Task ID 10790 | 0.0 |
Carry out general yard duties, such as performing shunting on railway lines.O*NET Task ID 10791 | 0.0 |
Adjust controls to guide, position, or move equipment, such as cranes, booms, or cameras.O*NET Task ID 10792 | 0.0 |
Guide loads being lifted to prevent swinging.O*NET Task ID 10793 | 0.0 |
Adjust or replace equipment parts, such as rollers, belts, plugs, or caps, using hand tools.O*NET Task ID 10794 | 0.0 |
Stack cargo in locations, such as transit sheds or in holds of ships as directed, using pallets or cargo boards.O*NET Task ID 10795 | 0.0 |
Connect electrical equipment to power sources so that it can be tested before use.O*NET Task ID 10796 | 0.0 |
Bundle and band material such as fodder or tobacco leaves, using banding machines.O*NET Task ID 10798 | 0.0 |
Rig or dismantle props or equipment, such as frames, scaffolding, platforms, or backdrops, using hand tools.O*NET Task ID 10799 | 0.0 |
Direct spouts and position receptacles, such as bins, carts, or containers, so they can be loaded.O*NET Task ID 10801 | 0.0 |
Wash out cargo containers or storage areas.O*NET Task ID 10804 | 0.0 |
Shovel material, such as gravel, ice, or spilled concrete, into containers or bins or onto conveyors.O*NET Task ID 10806 | 0.0 |
β = E1 + 0.5 × E2 · E1 = tasks where direct LLM access alone cuts time by at least 50%, E2 = tasks where software built on top of an LLM cuts time by at least 50%. Values take only 0 / 0.5 / 1.0.
Data sources & licenses — O*NET®, Anthropic Economic Index, Eloundou et al. (2023): see full notices on the Credits page